AI/ML Engineer Intern specializing in Machine Learning and Large Language Models (LLMs)

Job Description

“`html

Job Title: AI/ML Engineer Intern specializing in Machine Learning and Large Language Models (LLMs)

Introduction:

IBM Automation and AI group is actively seeking an AI/ML Engineer Intern, with a specialized focus on machine learning and Large Language Models (LLMs). This role is a vital addition to our AI/ML Center of Excellence team at the prestigious IBM Silicon Valley Lab location. As an intern, you will play a crucial role in collaborating with cross-functional product teams to implement state-of-the-art AI/ML capabilities across IBM’s extensive Automation product portfolio. Your contributions will involve leading efforts in data collection for LLM training and evaluation, seamlessly integrating LLM technologies into both existing and new products, and establishing best practices for AI/ML feature implementation across various product teams.

Your Role And Responsibilities:

• Data Collection and Management for LLM Evaluation and Training:
  • Design and implement robust data collection pipelines for diverse LLM training datasets, leveraging the IBM AI Model & Data Catalog.
  • Develop comprehensive data quality assessment frameworks to ensure training data consistently meets IBM’s rigorous standards.
  • Create precise annotation guidelines and efficient workflows for specialized, domain-specific datasets.
  • Implement stringent data governance protocols to ensure compliance with privacy regulations and ethical AI principles, strictly following the IBM Data & Model Governance process and tooling.
  • Establish robust evaluation datasets and benchmarks to accurately measure LLM performance across various use cases, leveraging tools such as FM-Eval and Unitxt.
• LLM Integration and Implementation:
  • Architect innovative solutions to integrate LLMs seamlessly with IBM’s existing and emerging products and broader ecosystem.
  • Develop powerful APIs and intuitive interfaces that enable seamless interaction between LLMs and other critical software components.
  • Optimize LLM deployment strategies for various computing environments, including cloud, edge, and on-premises solutions.
  • Implement advanced techniques for model compression, quantization, and optimization to significantly improve inference efficiency and minimize resource requirements.
  • Design and implement comprehensive prompt engineering frameworks to ensure consistent LLM behavior across all products.
• AI/ML Best Practices and Innovation:
  • Establish clear technical standards and best practices for the implementation of AI/ML features.
  • Create reusable components and effective design patterns for common LLM use cases.
  • Develop sophisticated monitoring systems to continuously track model performance, detect drift, and identify potential biases.
  • Research and implement cutting-edge techniques for responsible AI, including explainability and fairness.
  • Collaborate closely with product teams to identify compelling opportunities for AI-driven innovation.

Preferred Education:

• Bachelor’s Degree

Required Technical And Professional Expertise:

• Currently pursuing a Bachelor’s or Master’s degree or higher in Computer Science, Machine Learning, AI, or a related technical field.
• Less than one year of experience in machine learning engineering or data science roles.
• Demonstrated knowledge of NLP and large language models (e.g., transformer architectures), including expertise in model evaluation and algorithm design.
• Strong programming skills in Python and familiarity with key ML frameworks (PyTorch, TensorFlow, or JAX).
• Experience with data processing pipelines and working with large datasets.
• Knowledge of MLOps practices and tools for model deployment and monitoring.
• Ability to work independently and collaborate effectively across diverse teams.
• Strong communication skills to explain complex AI concepts to diverse audiences.
• A robust problem-solving mindset with the ability to navigate technical and business constraints.

Preferred Technical And Professional Experience:

• Currently pursuing a Bachelor’s or Master’s degree or higher in Computer Science, Machine Learning, AI, or a related technical field.
• Less than one year of experience in machine learning engineering or data science roles.
• Demonstrated knowledge of NLP and large language models (e.g., transformer architectures), including expertise in model evaluation and algorithm design.
• Strong programming skills in Python and familiarity with key ML frameworks (PyTorch, TensorFlow, or JAX).
• Experience with data processing pipelines and working with large datasets.
• Knowledge of MLOps practices and tools for model deployment and monitoring.
• Ability to work independently and collaborate effectively across diverse teams.
• Strong communication skills to explain complex AI concepts to diverse audiences.
• A robust problem-solving mindset with the ability to navigate technical and business constraints.

“`